Autonomous and semi-autonomous vehicles require robust systems for handling and responding to various conditions and hazards in their environments. Media responses to recent incidents involving current autonomous and/or semi-autonomous vehicles have focused on system-attributable failures (e.g., energy storage issues, semi-autonomous mode related incidents, etc.); however, without technology developments related to adaptive risk mitigation, future incidents will draw into question the ability of such autonomous systems to handle real-world driving conditions and hazards in a safe manner. In particular, improved risk modeling that can be used to provide adaptive and appropriate responses to transit-related factors in a timely manner will be crucial.
Current algorithms and systems, while under a state of improvement, currently lack an ability adequately account for or adapt to risks attributed to human factors, non-human factors, environmental factors, and other factors in an adaptive, comprehensive, and suitably responsive manner. Thus, there is a need in the vehicle telematics field to create a new and useful method and system for adaptive risk modeling. This invention provides such a new and useful system and method.